Monthly Traffic Safety Analysis

193 CRASHES IN
QUINCY, MA
NOVEMBER 2022

All metrics benchmarked againstNovember 2021

Total crashes in November 2022 were 193, a slight decrease from 194 crashes in November 2021. Despite the overall decrease in crashes, fatalities increased from 0 in November 2021 to 1 in November 2022. This represents a significant shift in crash outcomes year-over-year.

193

-0.5%was 194

Total Crash Events

1

Persons Killed

38

-11.6%was 43

Persons Injured

26

13.0%was 23

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 6 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes remained relatively stable, with a minor decrease of 0.52% from 194 crashes in November 2021 to 193 crashes in November 2022. However, total fatalities increased from 0 to 1, while total injuries decreased from 43 to 38 during the same period.

26

Hit-and-Run Crashes — November 2022

13.0% vs prior (23)

The number of hit-and-run crashes increased from 23 in November 2021 to 26 in November 2022. This resulted in an increase in the hit-and-run rate from 11.9% to 13.5% of all crashes. The data indicates an upward trend in hit-and-run incidents year-over-year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

5

Pedestrians Injured

Prior: 425.0%

2

Cyclists Injured

Prior: 0%

31

Motorists Injured

Prior: 39-20.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Thursday in November 2021 to Wednesday in November 2022. Similarly, the peak hour for crashes moved from 5 PM (18 crashes) in the prior period to 2 PM (21 crashes) in the current period. Crashes on Wednesday increased from 24 to 41, while crashes on Monday decreased from 32 to 21.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes increased from 0 in November 2021 to 1 in November 2022, resulting in a fatal rate of 0.5% of all crashes. Serious injury crashes decreased from 4 (2.1% share) to 1 (0.5% share) year-over-year. Minor injury crashes saw an increase from 20 (10.3% share) to 24 (12.4% share) in the current period.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.5%
Serious Injury1serious injury crashes0.5%
-75.0%prior 4
Minor Injury24minor injury crashes12.4%
20.0%prior 20
Possible Injury7possible injury crashes3.6%
0.0%prior 7
No Injury154no injury crashes79.8%
-3.1%prior 159

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Followed too closely" increased by 7, from 17 in November 2021 to 24 in November 2022. "Inattention" crashes slightly decreased by 2, from 67 to 65. Speeding-related crashes (from KPIs) increased by 5, from 5 in the prior period to 10 in the current period.

Officer-Reported Primary Contributing Cause

Inattention65 (33.7%)-3.0%prior 67
Followed too closely24 (12.4%)41.2%prior 17
No improper driving19 (9.8%)-9.5%prior 21
Failed to yield right of way14 (7.3%)-41.7%prior 24
Failure to keep in proper lane or running off road10 (5.2%)-9.1%prior 11
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner6 (3.1%)-14.3%prior 7
Driving too fast for conditions5 (2.6%)
Exceeded authorized speed limit4 (2.1%)
Over-correcting/over-steering4 (2.1%)
Other improper action3 (1.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased by 8, from 159 in November 2021 to 151 in November 2022. Conversely, crashes in rainy conditions increased by 5, from 16 to 21. Crashes during daylight hours increased by 8, while those in dark-lighted roadway conditions decreased by 9.

Weather

Clear130 (68.1%)
-5.1%prior 137
Clear/Clear21 (11.0%)
-4.5%prior 22
Rain20 (10.5%)
66.7%prior 12
Cloudy15 (7.9%)
0.0%prior 15
Cloudy/Cloudy3 (1.6%)
Cloudy/Fog, smog, smoke1 (0.5%)
Cloudy/Rain1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash

Lighting

Daylight119 (61.7%)
7.2%prior 111
Dark - lighted roadway63 (32.6%)
-12.5%prior 72
Dusk6 (3.1%)
20.0%prior 5
Dark - roadway not lighted4 (2.1%)
Dawn1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field

Road Surface

Dry166 (86.0%)
-2.4%prior 170
Wet27 (14.0%)
12.5%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes slightly increased from 372 to 377 year-over-year. Toyota vehicles involved in crashes decreased by 9 (from 80 to 71), while Honda vehicles increased by 3 (from 42 to 45). The 26-34 age group saw an increase of 10 persons involved in crashes (from 73 to 83), whereas the 65+ age group decreased by 10 (from 52 to 42).

Top Vehicle Makes (377 vehicles)

1
TOYOTA71 (18.8%)
-11.3%prior 80
2
HONDA45 (11.9%)
7.1%prior 42
3
FORD39 (10.3%)
-9.3%prior 43
4
NISSAN28 (7.4%)
7.7%prior 26
5
CHEVROLET27 (7.2%)
12.5%prior 24
6
JEEP18 (4.8%)
12.5%prior 16
7
SUBARU13 (3.4%)
160.0%prior 5
8
LEXUS12 (3.2%)
140.0%prior 5
9
MAZDA11 (2.9%)
10
BMW10 (2.7%)
-41.2%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records

51 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (441 persons with recorded sex)

Male238 (54.0%)
0.0%prior 238
Female202 (45.8%)
6.9%prior 189
R1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased by 4, from 32 in the prior period to 36 in the current period, and included one fatal crash in the current period compared to none prior. Crashes in 25 mph zones increased by 3, from 106 to 109, while crashes in 55 mph zones increased by 2, from 23 to 25. No fatal crashes were recorded in 25 mph or 55 mph zones in either period.

Fatal crashes by zone: 30 mph: 1 of 36 (2.778%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Posted speed limit at crash location

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: Arcgis_yearly Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2022-11-01 through 2022-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-11-01 through 2022-11-30 (30 days)
  • Geographic scope: QUINCY, MA
  • Total crash records analyzed: 193
  • Total persons involved: 482
  • Total vehicles involved: 377

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "QUINCY, MA Crash Intelligence Report: November 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/quincy/november-2022-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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Quincy, MA Crash Report — November 2022 | ThatCarHitMe.com